Lead Platform Engineer – Agentic System

Our organization is developing anAgentic AI Platformdesigned to orchestrate intelligent, autonomous workflows that drive decision-making, automation, and innovation across diverse domains. As theLead AI Platform Engineer , you will be responsible for architecting and implementing the foundational elements of this platform. This includes designing, deploying and maintaining production grademulti-agent systems with most effective frameworksincludingCrewAI, LangGraph , or equivalent systems, and deploying these solutions at scale on modern cloud infrastructure. You will work on and collaborate closely with other data engineers, data scientists, ML engineers, and product teams to realize our vision of adaptive, reasoning-driven systems. Key Responsibilities Architect & Build Agentic Systems:Design, develop, and deploy multi-agent workflows leveraging frameworks such asCrewAI, LangGraph , or custom-built orchestration layers. Platform Engineering:Construct the underlyingagentic runtime , encompassing message routing, memory management, and context-sharing mechanisms between agents. LLM & Tool Integration:Integrate Large Language Models (e.g., OpenAI, Anthropic, or open-source alternatives), vector databases, retrieval systems, and external APIs for agent tool-use and reasoning capabilities. Workflow Design & Optimization:Collaborate with AI researchers and solution engineers to design dynamic agent workflows that adapt based on contextual information and analytical results. Cloud & Scalability:Architect scalable, cost-efficient deployments utilizingAWS, GCP, or Azure , leveraging cloud-native components (e.g., Lambda, ECS, Kubernetes, Pub/Sub) to ensure high availability and performance. Observability & Governance:Implement comprehensive monitoring, evaluation metrics, and safety checks for autonomous agents to ensure reliability and compliance. Team Leadership & Mentorship:Provide guidance to a team of engineers, establish best practices for agent development, and cultivate a high-performance engineering culture. Take sessions for the team and build tog-grade skills in the area across the company. Required Qualifications Strong background in Python , with demonstrated experience in asynchronous programming, API development, and distributed systems. Proven experience in buildingLLM-powered multi-agent systemsusingCrewAI ,LangGraph ,LangChain , or similar orchestration frameworks. Deep understanding ofprompt engineering ,RAG pipelines , andtool-calling mechanisms . Hands-on experience withcloud infrastructure(AWS/GCP/Azure) andMLOpscomponents (e.g., Kubernetes, Docker, CI/CD, API Gateway). Solid understanding ofstate management ,context persistence , andmemory architecturefor agents. Experience integratingvector stores (e.g., FAISS, Pinecone, Chroma, Weaviate)andLLM APIs(e.g., OpenAI, Claude, Gemini). Demonstrated ability toarchitect scalable AI systemsfrom prototype to production. Excellent communication and collaboration skills, with the ability to translate complex technical concepts into actionable platform features. Experience withGraph-based orchestrationorLangGraph advanced workflows . Familiarity withCrewAI “crew and task” paradigmsor other agent coordination frameworks. Nice-to-Have Exposure toevent-driven architectures ,message queues , orknowledge graphs . Understanding ofAI safety, alignment , andgovernance principles . Contributions to open-source agent frameworks or AI orchestration tools. Ability to customize models to specific purposes. What We Offer An unparalleled opportunity tobuild the next-generation Agentic AI Platformfrom inception. The chance to work withcutting-edge LLM orchestration technologiesandcloud-native AI systems . Competitive compensation and potential equity options. A collaborative, innovation-driven culture with a strong focus on real-world impact